Recovering the input of a system from a noisy lecture of the output is both a typical inverse ill-posed problem and a transmission paradigm. If the input-output relation is given by a convolution integral, we are concerned with the well-known deconvolution problem, which occurs in several scientific frameworks. In this paper, we develop an original information-theoretic analysis and we design an encoding-decoding scheme for deconvolution. We propose different decoding algorithms to identify the input and we show both theoretical and simulations' results.
An Information Theoretic Approach to Hybrid Deconvolution Problems / Fosson, Sophie; Fagnani, Fabio. - ELETTRONICO. - 17:(2008), pp. 10112-10117. (Intervento presentato al convegno 17th IFAC World Congress tenutosi a COEX, Seoul, South Korea nel 06/07/2008-11/07/2008) [10.3182/20080706-5-KR-1001.01711].
An Information Theoretic Approach to Hybrid Deconvolution Problems
FOSSON, SOPHIE;FAGNANI, FABIO
2008
Abstract
Recovering the input of a system from a noisy lecture of the output is both a typical inverse ill-posed problem and a transmission paradigm. If the input-output relation is given by a convolution integral, we are concerned with the well-known deconvolution problem, which occurs in several scientific frameworks. In this paper, we develop an original information-theoretic analysis and we design an encoding-decoding scheme for deconvolution. We propose different decoding algorithms to identify the input and we show both theoretical and simulations' results.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2505133
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